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The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions.
Bognar, Katalin; Romley, John A; Bae, Jay P; Murray, James; Chou, Jacquelyn W; Lakdawalla, Darius N.
  • Bognar K; Precision Health Economics, Los Angeles, CA, United States.
  • Romley JA; University of Southern California, Los Angeles, CA, United States.
  • Bae JP; Eli Lilly & Company, Indianapolis, IN, United States.
  • Murray J; Eli Lilly & Company, Indianapolis, IN, United States.
  • Chou JW; Precision Health Economics, Los Angeles, CA, United States.
  • Lakdawalla DN; University of Southern California, Los Angeles, CA, United States. Electronic address: dlakdawa@usc.edu.
J Health Econ ; 51: 1-12, 2017 01.
Article en En | MEDLINE | ID: mdl-27992772
ABSTRACT
Approval of new drugs is increasingly reliant on "surrogate endpoints," which correlate with but imperfectly predict clinical benefits. Proponents argue surrogate endpoints allow for faster approval, but critics charge they provide inadequate evidence. We develop an economic framework that addresses the value of improvement in the predictive power, or "quality," of surrogate endpoints, and clarifies how quality can influence decisions by regulators, payers, and manufacturers. For example, the framework shows how lower-quality surrogates lead to greater misalignment of incentives between payers and regulators, resulting in more drugs that are approved for use but not covered by payers. Efficient price-negotiation in the marketplace can help align payer incentives for granting access based on surrogates. Higher-quality surrogates increase manufacturer profits and social surplus from early access to new drugs. Since the return on better quality is shared between manufacturers and payers, private incentives to invest in higher-quality surrogates are inefficiently low.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biomarcadores / Aprobación de Drogas / Cobertura del Seguro Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2017 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biomarcadores / Aprobación de Drogas / Cobertura del Seguro Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2017 Tipo del documento: Article